Recently, entropy minimization has been widely used in semi-supervised learning to utilize the unlabeled data [1]}, [2]}, [3]}. It encourages the model to produce high confidence prediction by minimizing the following object function:
\(\mathcal {L}_{ent} = \sum _{c} \sum _{i} -p_c^i \cdot \log {p_c^i}\) 
